Systems and methods for determining customer state transitions for growth of customer lifetime values

ABSTRACT

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of determining a lifetime value (LTV) for customers of a retailer, segmenting the customers into customer states based upon one or more purchases made by each customer at the retailer within a predetermined period of time, determining a first average LTV for customers in a first customer state and a second average LTV for customers in a second customer state lower than the first average LTV, coordinating a first display of a first online advertisement for customers in the first LTV to transition the customers from the first customer state to the second customer state, and coordinating a second display of a second online advertisement for customers in the second state.

TECHNICAL FIELD

This disclosure relates generally to systems and methods for customerstate transitions for growth of customer lifetime values.

BACKGROUND

A lifetime value (LTV) is used to predict a customer's future value witha company or retailer. Identification of overall LTV growth paths forall customers can be useful for overall growth of a retailer.Identifying incremental growth of an LTV for an individual customer,however, can be very difficult. Conventional systems and methods foridentifying incremental growth of an LTV for an individual customertypically result in non-continuous functions, making estimation ofderivatives very difficult.

BRIEF DESCRIPTION OF THE DRAWINGS

To facilitate further description of the embodiments, the followingdrawings are provided in which:

FIG. 1 illustrates a front elevational view of a computer system that issuitable for implementing various embodiments of the systems disclosedin FIGS. 3 and 6;

FIG. 2 illustrates a representative block diagram of an example of theelements included in the circuit boards inside a chassis of the computersystem of FIG. 1;

FIG. 3 illustrates a representative block diagram of a system, accordingto an embodiment;

FIGS. 4A-B are flowcharts for a method, according to certainembodiments;

FIG. 5 is a flowchart for a method, according to additional embodiments;

FIG. 6 illustrates a representative block diagram of a portion of thesystem of FIG. 3, according to an embodiment.

For simplicity and clarity of illustration, the drawing figuresillustrate the general manner of construction, and descriptions anddetails of well-known features and techniques may be omitted to avoidunnecessarily obscuring the present disclosure. Additionally, elementsin the drawing figures are not necessarily drawn to scale. For example,the dimensions of some of the elements in the figures may be exaggeratedrelative to other elements to help improve understanding of embodimentsof the present disclosure. The same reference numerals in differentfigures denote the same elements.

The terms “first,” “second,” “third,” “fourth,” and the like in thedescription and in the claims, if any, are used for distinguishingbetween similar elements and not necessarily for describing a particularsequential or chronological order. It is to be understood that the termsso used are interchangeable under appropriate circumstances such thatthe embodiments described herein are, for example, capable of operationin sequences other than those illustrated or otherwise described herein.Furthermore, the terms “include,” and “have,” and any variationsthereof, are intended to cover a non-exclusive inclusion, such that aprocess, method, system, article, device, or apparatus that comprises alist of elements is not necessarily limited to those elements, but mayinclude other elements not expressly listed or inherent to such process,method, system, article, device, or apparatus.

The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,”“under,” and the like in the description and in the claims, if any, areused for descriptive purposes and not necessarily for describingpermanent relative positions. It is to be understood that the terms soused are interchangeable under appropriate circumstances such that theembodiments of the apparatus, methods, and/or articles of manufacturedescribed herein are, for example, capable of operation in otherorientations than those illustrated or otherwise described herein.

The terms “couple,” “coupled,” “couples,” “coupling,” and the likeshould be broadly understood and refer to connecting two or moreelements mechanically and/or otherwise. Two or more electrical elementsmay be electrically coupled together, but not be mechanically orotherwise coupled together. Coupling may be for any length of time,e.g., permanent or semi-permanent or only for an instant. “Electricalcoupling” and the like should be broadly understood and includeelectrical coupling of all types. The absence of the word “removably,”“removable,” and the like near the word “coupled,” and the like does notmean that the coupling, etc. in question is or is not removable.

As defined herein, two or more elements are “integral” if they arecomprised of the same piece of material. As defined herein, two or moreelements are “non-integral” if each is comprised of a different piece ofmaterial.

As defined herein, “real-time” can, in some embodiments, be defined withrespect to operations carried out as soon as practically possible uponoccurrence of a triggering event. A triggering event can include receiptof data necessary to execute a task or to otherwise process information.Because of delays inherent in transmission and/or in computing speeds,the term “real time” encompasses operations that occur in “near” realtime or somewhat delayed from a triggering event. In a number ofembodiments, “real time” can mean real time less a time delay forprocessing (e.g., determining) and/or transmitting data. The particulartime delay can vary depending on the type and/or amount of the data, theprocessing speeds of the hardware, the transmission capability of thecommunication hardware, the transmission distance, etc. However, in manyembodiments, the time delay can be less than approximately one second,two seconds, five seconds, or ten seconds.

As defined herein, “approximately” can, in some embodiments, mean withinplus or minus ten percent of the stated value. In other embodiments,“approximately” can mean within plus or minus five percent of the statedvalue. In further embodiments, “approximately” can mean within plus orminus three percent of the stated value. In yet other embodiments,“approximately” can mean within plus or minus one percent of the statedvalue.

DESCRIPTION OF EXAMPLES OF EMBODIMENTS

A number of embodiments can include a system. The system can include oneor more processing modules and one or more non-transitory storagemodules storing computing instructions configured to run on the one ormore processing modules. The one or more storage modules can beconfigured to run on the one or more processing modules and perform anact of determining, for each customer of a plurality of customers, a LTVfor a retailer. The one or more storage modules can be furtherconfigured to run on the one or more processing modules and perform anact of segmenting the plurality of customers into a plurality ofcustomer states based upon one or more purchases made by each customerof the plurality of customers at the retailer within a predeterminedperiod of time such that one or more first customers of the plurality ofcustomers are segmented into a first customer state of the plurality ofcustomer states and one or more second customers of the plurality ofcustomers are segmented into a second customer state of the plurality ofcustomer states. The one or more storage modules can be furtherconfigured to run on the one or more processing modules and perform anact of determining a first average LTV for the one or more firstcustomers and a second average LTV for the one or more second customers,wherein the first average LTV is a lower number than the second LTV. Theone or more storage modules can be further configured to run on the oneor more processing modules and perform an act of coordinating a firstdisplay of a first online advertisement for the one or more firstcustomers to transition the one or more first customers from the firstcustomer state to the second customer state. The one or more storagemodules can be further configured to run on the one or more processingmodules and perform an act of coordinating a second display of a secondonline advertisement for the one or more second customers.

Various embodiments include a method. The method can includedetermining, for each customer of a plurality of customers, a LTV for aretailer. The method also can include segmenting the plurality ofcustomers into a plurality of customer states based upon one or morepurchases made by each customer of the plurality of customers at theretailer within a predetermined period of time such that one or morefirst customers of the plurality of customers are segmented into a firstcustomer state of the plurality of customer states and one or moresecond customers of the plurality of customers are segmented into asecond customer state of the plurality of customer states. The methodalso can include determining a first average LTV for the one or morefirst customers and a second average LTV for the one or more secondcustomers, wherein the first average LTV is a lower number than thesecond LTV. The method also can include coordinating a first display ofa first online advertisement for the one or more first customers totransition the one or more first customers from the first customer stateto the second customer state. The method also can include coordinating asecond display of a second online advertisement for the one or moresecond customers.

Turning to the drawings, FIG. 1 illustrates an exemplary embodiment of acomputer system 100, all of which or a portion of which can be suitablefor (i) implementing part or all of one or more embodiments of thetechniques, methods, and systems and/or (ii) implementing and/oroperating part or all of one or more embodiments of the memory storagemodules described herein. As an example, a different or separate one ofa chassis 102 (and its internal components) can be suitable forimplementing part or all of one or more embodiments of the techniques,methods, and/or systems described herein. Furthermore, one or moreelements of computer system 100 (e.g., a monitor 106, a keyboard 104,and/or a mouse 110, etc.) also can be appropriate for implementing partor all of one or more embodiments of the techniques, methods, and/orsystems described herein. Computer system 100 can comprise chassis 102containing one or more circuit boards (not shown), a Universal SerialBus (USB) port 112, a Compact Disc Read-Only Memory (CD-ROM) and/orDigital Video Disc (DVD) drive 116, and a hard drive 114. Arepresentative block diagram of the elements included on the circuitboards inside chassis 102 is shown in FIG. 2. A central processing unit(CPU) 210 in FIG. 2 is coupled to a system bus 214 in FIG. 2. In variousembodiments, the architecture of CPU 210 can be compliant with any of avariety of commercially distributed architecture families.

Continuing with FIG. 2, system bus 214 also is coupled to a memorystorage unit 208, where memory storage unit 208 can comprise (i)volatile (e.g., transitory) memory, such as, for example, read onlymemory (ROM) and/or (ii) non-volatile (e.g., non-transitory) memory,such as, for example, random access memory (RAM). The non-volatilememory can be removable and/or non-removable non-volatile memory.Meanwhile, RAM can include dynamic RAM (DRAM), static RAM (SRAM), etc.Further, ROM can include mask-programmed ROM, programmable ROM (PROM),one-time programmable ROM (OTP), erasable programmable read-only memory(EPROM), electrically erasable programmable ROM (EEPROM) (e.g.,electrically alterable ROM (EAROM) and/or flash memory), etc. The memorystorage module(s) of the various embodiments disclosed herein cancomprise memory storage unit 208, an external memory storage drive (notshown), such as, for example, a USB-equipped electronic memory storagedrive coupled to universal serial bus (USB) port 112 (FIGS. 1-2), harddrive 114 (FIGS. 1-2), a CD-ROM and/or DVD for use with CD-ROM and/orDVD drive 116 (FIGS. 1-2), a floppy disk for use with a floppy diskdrive (not shown), an optical disc (not shown), a magneto-optical disc(now shown), magnetic tape (not shown), etc. Further, non-volatile ornon-transitory memory storage module(s) refer to the portions of thememory storage module(s) that are non-volatile (e.g., non-transitory)memory.

In various examples, portions of the memory storage module(s) of thevarious embodiments disclosed herein (e.g., portions of the non-volatilememory storage module(s)) can be encoded with a boot code sequencesuitable for restoring computer system 100 (FIG. 1) to a functionalstate after a system reset. In addition, portions of the memory storagemodule(s) of the various embodiments disclosed herein (e.g., portions ofthe non-volatile memory storage module(s)) can comprise microcode suchas a Basic Input-Output System (BIOS) operable with computer system 100(FIG. 1). In the same or different examples, portions of the memorystorage module(s) of the various embodiments disclosed herein (e.g.,portions of the non-volatile memory storage module(s)) can comprise anoperating system, which can be a software program that manages thehardware and software resources of a computer and/or a computer network.The BIOS can initialize and test components of computer system 100(FIG. 1) and load the operating system. Meanwhile, the operating systemcan perform basic tasks such as, for example, controlling and allocatingmemory, prioritizing the processing of instructions, controlling inputand output devices, facilitating networking, and managing files.Exemplary operating systems can comprise one of the following: (i)Microsoft® Windows® operating system (OS) by Microsoft Corp. of Redmond,Wash., United States of America, (ii) Mac® OS X by Apple Inc. ofCupertino, Calif., United States of America, (iii) UNIX® OS, and (iv)Linux® OS. Further exemplary operating systems can comprise one of thefollowing: (i) the iOS® operating system by Apple Inc. of Cupertino,Calif., United States of America, (ii) the Blackberry® operating systemby Research In Motion (RIM) of Waterloo, Ontario, Canada, (iii) theWebOS operating system by LG Electronics of Seoul, South Korea, (iv) theAndroid™ operating system developed by Google, of Mountain View, Calif.,United States of America, (v) the Windows Mobile™ operating system byMicrosoft Corp. of Redmond, Wash., United States of America, or (vi) theSymbian™ operating system by Accenture PLC of Dublin, Ireland.

As used herein, “processor” and/or “processing module” means any type ofcomputational circuit, such as but not limited to a microprocessor, amicrocontroller, a controller, a complex instruction set computing(CISC) microprocessor, a reduced instruction set computing (RISC)microprocessor, a very long instruction word (VLIW) microprocessor, agraphics processor, a digital signal processor, or any other type ofprocessor or processing circuit capable of performing the desiredfunctions. In some examples, the one or more processing modules of thevarious embodiments disclosed herein can comprise CPU 210.

Alternatively, or in addition to, the systems and procedures describedherein can be implemented in hardware, or a combination of hardware,software, and/or firmware. For example, one or more application specificintegrated circuits (ASICs) can be programmed to carry out one or moreof the systems and procedures described herein. For example, one or moreof the programs and/or executable program components described hereincan be implemented in one or more ASICs. In many embodiments, anapplication specific integrated circuit (ASIC) can comprise one or moreprocessors or microprocessors and/or memory blocks or memory storage.

In the depicted embodiment of FIG. 2, various I/O devices such as a diskcontroller 204, a graphics adapter 224, a video controller 202, akeyboard adapter 226, a mouse adapter 206, a network adapter 220, andother I/O devices 222 can be coupled to system bus 214. Keyboard adapter226 and mouse adapter 206 are coupled to keyboard 104 (FIGS. 1-2) andmouse 110 (FIGS. 1-2), respectively, of computer system 100 (FIG. 1).While graphics adapter 224 and video controller 202 are indicated asdistinct units in FIG. 2, video controller 202 can be integrated intographics adapter 224, or vice versa in other embodiments. Videocontroller 202 is suitable for monitor 106 (FIGS. 1-2) to display imageson a screen 108 (FIG. 1) of computer system 100 (FIG. 1). Diskcontroller 204 can control hard drive 114 (FIGS. 1-2), USB port 112(FIGS. 1-2), and CD-ROM drive 116 (FIGS. 1-2). In other embodiments,distinct units can be used to control each of these devices separately.

Network adapter 220 can be suitable to connect computer system 100(FIG. 1) to a computer network by wired communication (e.g., a wirednetwork adapter) and/or wireless communication (e.g., a wireless networkadapter). In some embodiments, network adapter 220 can be plugged orcoupled to an expansion port (not shown) in computer system 100 (FIG.1). In other embodiments, network adapter 220 can be built into computersystem 100 (FIG. 1). For example, network adapter 220 can be built intocomputer system 100 (FIG. 1) by being integrated into the motherboardchipset (not shown), or implemented via one or more dedicatedcommunication chips (not shown), connected through a PCI (peripheralcomponent interconnector) or a PCI express bus of computer system 100(FIG. 1) or USB port 112 (FIG. 1).

Returning now to FIG. 1, although many other components of computersystem 100 are not shown, such components and their interconnection arewell known to those of ordinary skill in the art. Accordingly, furtherdetails concerning the construction and composition of computer system100 and the circuit boards inside chassis 102 are not discussed herein.

Meanwhile, when computer system 100 is running, program instructions(e.g., computer instructions) stored on one or more of the memorystorage module(s) of the various embodiments disclosed herein can beexecuted by CPU 210 (FIG. 2). At least a portion of the programinstructions, stored on these devices, can be suitable for carrying outat least part of the techniques and methods described herein.

Further, although computer system 100 is illustrated as a desktopcomputer in FIG. 1, there can be examples where computer system 100 maytake a different form factor while still having functional elementssimilar to those described for computer system 100. In some embodiments,computer system 100 may comprise a single computer, a single server, ora cluster or collection of computers or servers, or a cloud of computersor servers. Typically, a cluster or collection of servers can be usedwhen the demand on computer system 100 exceeds the reasonable capabilityof a single server or computer. In certain embodiments, computer system100 may comprise a portable computer, such as a laptop computer. Incertain other embodiments, computer system 100 may comprise a mobileelectronic device, such as a smartphone. In certain additionalembodiments, computer system 100 may comprise an embedded system.

Turning ahead in the drawings, FIG. 3 illustrates a block diagram of asystem 300 that can be employed for determining customer LTV, asdescribed in greater detail below. System 300 is merely exemplary andembodiments of the system are not limited to the embodiments presentedherein. System 300 can be employed in many different embodiments orexamples not specifically depicted or described herein. In someembodiments, certain elements or modules of system 300 can performvarious procedures, processes, and/or activities. In these or otherembodiments, the procedures, processes, and/or activities can beperformed by other suitable elements or modules of system 300.

Generally, therefore, system 300 can be implemented with hardware and/orsoftware, as described herein. In some embodiments, part or all of thehardware and/or software can be conventional, while in these or otherembodiments, part or all of the hardware and/or software can becustomized (e.g., optimized) for implementing part or all of thefunctionality of system 300 described herein.

In some embodiments, system 300 can include a LTV system 310, a webserver 320, a display system 360, and/or a customer state system 370.LTV system 310, web server 320, display system 360, and/or customerstate system 370 can each be a computer system, such as computer system100 (FIG. 1), as described above, and can each be a single computer, asingle server, or a cluster or collection of computers or servers, or acloud of computers or servers. In another embodiment, a single computersystem can host each of two or more of LTV system 310, web server 320,display system 360, and/or customer state system 370. Additional detailsregarding LTV system 310, web server 320, display system 360, and/orcustomer state system 370 are described herein.

In many embodiments, system 300 also can comprise user computers 340,341. In some embodiments, user computers 340, 341 can be a mobiledevice. A mobile electronic device can refer to a portable electronicdevice (e.g., an electronic device easily conveyable by hand by a personof average size) with the capability to present audio and/or visual data(e.g., text, images, videos, music, etc.). For example, a mobileelectronic device can comprise at least one of a digital media player, acellular telephone (e.g., a smartphone), a personal digital assistant, ahandheld digital computer device (e.g., a tablet personal computerdevice), a laptop computer device (e.g., a notebook computer device, anetbook computer device), a wearable user computer device, or anotherportable computer device with the capability to present audio and/orvisual data (e.g., images, videos, music, etc.). Thus, in many examples,a mobile electronic device can comprise a volume and/or weightsufficiently small as to permit the mobile electronic device to beeasily conveyable by hand. For examples, in some embodiments, a mobileelectronic device can occupy a volume of less than or equal toapproximately 1790 cubic centimeters, 2434 cubic centimeters, 2876 cubiccentimeters, 4056 cubic centimeters, and/or 5752 cubic centimeters.Further, in these embodiments, a mobile electronic device can weigh lessthan or equal to 15.6 Newtons, 17.8 Newtons, 22.3 Newtons, 31.2 Newtons,and/or 44.5 Newtons.

Exemplary mobile electronic devices can comprise (i) an iPod®, iPhone®,iTouch®, iPad®, MacBook® or similar product by Apple Inc. of Cupertino,Calif., United States of America, (ii) a Blackberry® or similar productby Research in Motion (RIM) of Waterloo, Ontario, Canada, (iii) a Lumia®or similar product by the Nokia Corporation of Keilaniemi, Espoo,Finland, and/or (iv) a Galaxy™ or similar product by the Samsung Groupof Samsung Town, Seoul, South Korea. Further, in the same or differentembodiments, a mobile electronic device can comprise an electronicdevice configured to implement one or more of (i) the iPhone® operatingsystem by Apple Inc. of Cupertino, Calif., United States of America,(ii) the Blackberry® operating system by Research In Motion (RIM) ofWaterloo, Ontario, Canada, (iii) the Palm® operating system by Palm,Inc. of Sunnyvale, Calif., United States, (iv) the Android™ operatingsystem developed by the Open Handset Alliance, (v) the Windows Mobile™operating system by Microsoft Corp. of Redmond, Wash., United States ofAmerica, or (vi) the Symbian™ operating system by Nokia Corp. ofKeilaniemi, Espoo, Finland.

Further still, the term “wearable user computer device” as used hereincan refer to an electronic device with the capability to present audioand/or visual data (e.g., text, images, videos, music, etc.) that isconfigured to be worn by a user and/or mountable (e.g., fixed) on theuser of the wearable user computer device (e.g., sometimes under or overclothing; and/or sometimes integrated with and/or as clothing and/oranother accessory, such as, for example, a hat, eyeglasses, a wristwatch, shoes, etc.). In many examples, a wearable user computer devicecan comprise a mobile electronic device, and vice versa. However, awearable user computer device does not necessarily comprise a mobileelectronic device, and vice versa.

In specific examples, a wearable user computer device can comprise ahead mountable wearable user computer device (e.g., one or more headmountable displays, one or more eyeglasses, one or more contact lenses,one or more retinal displays, etc.) or a limb mountable wearable usercomputer device (e.g., a smart watch). In these examples, a headmountable wearable user computer device can be mountable in closeproximity to one or both eyes of a user of the head mountable wearableuser computer device and/or vectored in alignment with a field of viewof the user.

In more specific examples, a head mountable wearable user computerdevice can comprise (i) Google Glass™ product or a similar product byGoogle Inc. of Menlo Park, Calif., United States of America; (ii) theEye Tap™ product, the Laser Eye Tap™ product, or a similar product byePI Lab of Toronto, Ontario, Canada, and/or (iii) the Raptyr™ product,the STAR1200™ product, the Vuzix Smart Glasses M100™ product, or asimilar product by Vuzix Corporation of Rochester, N.Y., United Statesof America. In other specific examples, a head mountable wearable usercomputer device can comprise the Virtual Retinal Display™ product, orsimilar product by the University of Washington of Seattle, Wash.,United States of America. Meanwhile, in further specific examples, alimb mountable wearable user computer device can comprise the iWatch™product, or similar product by Apple Inc. of Cupertino, Calif., UnitedStates of America, the Galaxy Gear or similar product of Samsung Groupof Samsung Town, Seoul, South Korea, the Moto 360 product or similarproduct of Motorola of Schaumburg, Ill., United States of America,and/or the Zip™ product, One™ product, Flex™ product, Charge™ product,Surge™ product, or similar product by Fitbit Inc. of San Francisco,Calif., United States of America.

In some embodiments, web server 320 can be in data communication throughInternet 330 with user computers (e.g., 340, 341). In certainembodiments, user computers 340-341 can be desktop computers, laptopcomputers, smart phones, tablet devices, and/or other endpoint devices.Web server 320 can host one or more websites. For example, web server320 can host an eCommerce website that allows users to browse and/orsearch for products, to add products to an electronic shopping cart,and/or to purchase products, in addition to other suitable activities.

In many embodiments, LTV system 310, web server 320, display system 360,and/or customer state system 370 can each comprise one or more inputdevices (e.g., one or more keyboards, one or more keypads, one or morepointing devices such as a computer mouse or computer mice, one or moretouchscreen displays, a microphone, etc.), and/or can each comprise oneor more display devices (e.g., one or more monitors, one or more touchscreen displays, projectors, etc.). In these or other embodiments, oneor more of the input device(s) can be similar or identical to keyboard104 (FIG. 1) and/or a mouse 110 (FIG. 1). Further, one or more of thedisplay device(s) can be similar or identical to monitor 106 (FIG. 1)and/or screen 108 (FIG. 1). The input device(s) and the displaydevice(s) can be coupled to the processing module(s) and/or the memorystorage module(s) LTV system 310, web server 320, display system 360,and/or customer state system 370 in a wired manner and/or a wirelessmanner, and the coupling can be direct and/or indirect, as well aslocally and/or remotely. As an example of an indirect manner (which mayor may not also be a remote manner), a keyboard-video-mouse (KVM) switchcan be used to couple the input device(s) and the display device(s) tothe processing module(s) and/or the memory storage module(s). In someembodiments, the KVM switch also can be part of LTV system 310, webserver 320, display system 360, and/or customer state system 370. In asimilar manner, the processing module(s) and the memory storagemodule(s) can be local and/or remote to each other.

In many embodiments, LTV system 310, web server 320, display system 360,and/or customer state system 370 can be configured to communicate withone or more user computers 340 and 341. In some embodiments, usercomputers 340 and 341 also can be referred to as customer computers. Insome embodiments, LTV system 310, web server 320, display system 360,and/or customer state system 370 can communicate or interface (e.g.,interact) with one or more customer computers (such as user computers340 and 341) through a network or internet 330. Internet 330 can be anintranet that is not open to the public. Accordingly, in manyembodiments, LTV system 310, web server 320, display system 360, and/orcustomer state system 370 (and/or the software used by such systems) canrefer to a back end of system 300 operated by an operator and/oradministrator of system 300, and user computers 340 and 341 (and/or thesoftware used by such systems) can refer to a front end of system 300used by one or more users 350 and 351, respectively. In someembodiments, users 350 and 351 also can be referred to as customers, inwhich case, user computers 340 and 341 can be referred to as customercomputers. In these or other embodiments, the operator and/oradministrator of system 300 can manage system 300, the processingmodule(s) of system 300, and/or the memory storage module(s) of system300 using the input device(s) and/or display device(s) of system 300.

Meanwhile, in many embodiments, LTV system 310, web server 320, displaysystem 360, and/or customer state system 370 also can be configured tocommunicate with one or more databases. The one or more databases cancomprise a product database that contains information about products,items, or SKUs (stock keeping units) sold by a retailer. The one or moredatabases can be stored on one or more memory storage modules (e.g.,non-transitory memory storage module(s)), which can be similar oridentical to the one or more memory storage module(s) (e.g.,non-transitory memory storage module(s)) described above with respect tocomputer system 100 (FIG. 1). Also, in some embodiments, for anyparticular database of the one or more databases, that particulardatabase can be stored on a single memory storage module of the memorystorage module(s), and/or the non-transitory memory storage module(s)storing the one or more databases or the contents of that particulardatabase can be spread across multiple ones of the memory storagemodule(s) and/or non-transitory memory storage module(s) storing the oneor more databases, depending on the size of the particular databaseand/or the storage capacity of the memory storage module(s) and/ornon-transitory memory storage module(s).

The one or more databases can each comprise a structured (e.g., indexed)collection of data and can be managed by any suitable databasemanagement systems configured to define, create, query, organize,update, and manage database(s). Exemplary database management systemscan include MySQL (Structured Query Language) Database, PostgreSQLDatabase, Microsoft SQL Server Database, Oracle Database, SAP (Systems,Applications, & Products) Database, and IBM DB2 Database.

Meanwhile, communication between LTV system 310, web server 320, displaysystem 360, and/or customer state system 370, and/or the one or moredatabases can be implemented using any suitable manner of wired and/orwireless communication. Accordingly, system 300 can comprise anysoftware and/or hardware components configured to implement the wiredand/or wireless communication. Further, the wired and/or wirelesscommunication can be implemented using any one or any combination ofwired and/or wireless communication network topologies (e.g., ring,line, tree, bus, mesh, star, daisy chain, hybrid, etc.) and/or protocols(e.g., personal area network (PAN) protocol(s), local area network (LAN)protocol(s), wide area network (WAN) protocol(s), cellular networkprotocol(s), powerline network protocol(s), etc.). Exemplary PANprotocol(s) can comprise Bluetooth, Zigbee, Wireless Universal SerialBus (USB), Z-Wave, etc.; exemplary LAN and/or WAN protocol(s) cancomprise Institute of Electrical and Electronic Engineers (IEEE) 802.3(also known as Ethernet), IEEE 802.11 (also known as WiFi), etc.; andexemplary wireless cellular network protocol(s) can comprise GlobalSystem for Mobile Communications (GSM), General Packet Radio Service(GPRS), Code Division Multiple Access (CDMA), Evolution-Data Optimized(EV-DO), Enhanced Data Rates for GSM Evolution (EDGE), Universal MobileTelecommunications System (UMTS), Digital Enhanced CordlessTelecommunications (DECT), Digital AMPS (IS-136/Time Division MultipleAccess (TDMA)), Integrated Digital Enhanced Network (iDEN), EvolvedHigh-Speed Packet Access (HSPA+), Long-Term Evolution (LTE), WiMAX, etc.The specific communication software and/or hardware implemented candepend on the network topologies and/or protocols implemented, and viceversa. In many embodiments, exemplary communication hardware cancomprise wired communication hardware including, for example, one ormore data buses, such as, for example, universal serial bus(es), one ormore networking cables, such as, for example, coaxial cable(s), opticalfiber cable(s), and/or twisted pair cable(s), any other suitable datacable, etc. Further exemplary communication hardware can comprisewireless communication hardware including, for example, one or moreradio transceivers, one or more infrared transceivers, etc. Additionalexemplary communication hardware can comprise one or more networkingcomponents (e.g., modulator-demodulator components, gateway components,etc.).

Turning ahead in the drawings, FIGS. 4A-B illustrate flowcharts for amethod 400, according to an embodiment. Method 400 is merely exemplaryand is not limited to the embodiments presented herein. Method 400 canbe employed in many different embodiments or examples not specificallydepicted or described herein. In some embodiments, the activities ofmethod 400 can be performed in the order presented. In otherembodiments, the activities of method 400 can be performed in anysuitable order. In still other embodiments, one or more of theactivities of method 400 can be combined or skipped. In manyembodiments, system 300 (FIG. 3) can be suitable to perform method 400and/or one or more of the activities of method 400. In these or otherembodiments, one or more of the activities of method 400 can beimplemented as one or more computer instructions configured to run atone or more processing modules and configured to be stored at one ormore non-transitory memory storage modules 612, 614, 616, 618, 662and/or 672 (FIG. 6). Such non-transitory memory storage modules can bepart of a computer system such as LTV system 310, web server 320,display system 360, and/or customer state system 370 (FIGS. 3 & 6). Theprocessing module(s) can be similar or identical to the processingmodule(s) described above with respect to computer system 100 (FIG. 1).

Certain embodiments of method 400 can comprise a two-stage machinelearning LTV prediction framework that can be used for large-scalecustomer databases based on omni-channel interaction and transactiondata. The LTV prediction framework described herein can be applied toboth existing and potential customers. As described in greater detailbelow, omni-channel interaction and transaction data can comprise datafrom both online sources and offline sources. Generally, LTV for acustomer can comprise long-term metrics that predict the customer'sfuture value with a company. In certain embodiments, a LTV for acustomer can be based on eighteen total indices, including threemetrics, two aggregation levels, and three time windows. The threemetrics can comprise a (1) gross merchandise volume (GMV) or revenue,(2) a number of orders made by the customer, and (3) a retentionprobability, or other metrics. The two aggregation levels can compriseconsumable products, durable products, or other types of products.Consumable products can comprise products that consumers typically userecurrently and that can be used up, discarded, or can become expired.Durable products are products that do not wear out quickly, or thatyield utility over time rather than being completely consumed in one useor a short period of time. In some embodiments, the LTV update modelsdescribed below can be trained to apply to customers who have purchasedonly durable products, customers who have purchased only consumableproducts, and/or both durable and consumable products. The three timewindow can comprise 90 days, 180 days, 365 days, or other time periods.

Conventional methods and systems for determining LTVs for customers arebased entirely on historical transactions for a customer. Embodiments ofmethod 400 advantageously can take into account both online and offlinetransactions (or only one of online or offline transactions) for acustomer, as well as other non-transactional interactions. These othernon-transactional interactions can be helpful in determining a LTV for acustomer because potential customers can sometimes make multiple visitsto a website or store before purchasing an advertised product. LTVs forcustomers can be used in determining which advertisements of a pluralityof advertisement will be most effective for a particular customer and/ormost valuable to the retailer.

Turning to FIG. 4A, in some embodiments method 400 can comprise anactivity 405 of storing customer information in a customer database of aretailer. The plurality of customers can comprise a plurality ofpreexisting customers and/or a plurality of potential customers. Thecustomer information for each customer of the plurality of customers cancomprise (1) demographic information, (2) online interactioninformation, and/or (3) transaction information comprising online storetransaction information and offline store transaction information.Demographic information can comprise but is not limited to age, gender,income household size, location, and the like. Online interactioninformation can comprise but is not limited to a number of webpage viewsand/or searches in certain product categories in a past number ofpredetermined days that can be attributed to certain marketing channels.Other examples of online interactions can comprise visiting the websiteof a retailer via search engine marketing, registering for an accountwith the website of the retailer, receiving a marketing email from theretailer, clicking on an advertisement in an email from the retailer,shopping at a brick and mortar store of the retailer, and/or downloadinga mobile application for the retailer. Transaction information cancomprise but is not limited to a number of orders and/or GMV in certainproduct categories in a past number of predetermined days that can beattributed to certain marketing channels. All the transactioninformation and interaction information can be collected for allbusiness channels, for example a desktop website for the retailer, amobile website for the retailer, a mobile application for the retailer,and/or a brick and mortar store for the retailer (or offline store).

Continuing with FIG. 4A, method 400 further can comprise an activity 410of determining whether each customer of the plurality of customers had(1) an online store transaction with the retailer, (2) an offline storetransaction with the retailer, and/or (3) an online interaction with theretailer within a first predetermined period of time. The firstpredetermined period of time can comprise one day in some embodiments.In other embodiments, the first predetermined period of time cancomprise between one and three days, between three days and six days,one week, or one month.

After determining whether each customer had a transaction or interactionwith the retailer within a predetermined period of time, the pluralityof customers can be divided or categorized into two groups: (1)customers that have had an interaction or transaction with the retailerwithin the predetermined period of time; and (2) customers that have nothad an interaction or transaction with the retailer within thepredetermined period of time. Thus, continuing with FIG. 4A, method 400further can comprise an activity 415 of categorizing one or more firstcustomers of the plurality of customers into a first customer group ifthe one or more first customers had (1) the online store transactionwith the retailer, (2) the offline store transaction with the retailer,and/or (3) the online interaction with the retailer within the firstpredetermined period of time. Method 400 further can comprise anactivity 420 of categorizing one or more second customers of theplurality of customers into a second customer group if the one or moresecond customers did not have (1) the online store transaction with theretailer, (2) the offline store transaction with the retailer, and/or(3) the online interaction with the retailer within the firstpredetermined period of time.

Customers that have had an interaction or transaction with the retailerwithin the predetermined period of time can have their LTV updated toreflect a new LTV using an LTV update model. As noted above, a LTV for acustomer can be based on: (1) a predicted gross merchandise volumevalue; (2) a predicted number of orders; (3) a retention probability;(4) consumable products purchased; (5) durable products purchased;and/or (6) a predetermined window of time comprising one of 90 days, 180days, or 365 days. Interactions and/or transaction by the customer withthe online retailer can, therefore, affect a LTV for the customer. Thus,continuing with FIG. 4A, method 400 further can comprise an activity 425of predicting, using a LTV update model, a LTV for each of the one ormore first customers of the first customer group.

For customers who have made a purchase within the predetermined periodof time, a two-stage approach can be utilized to estimate an updatedLTV. Certain embodiments of the two-stage approach are beneficial tocomputer systems and networks because the two-stage approach describedherein reduces an amount of time needed to determine or otherwisepredict GMV and numbers of orders for a customer, thus allowing thecomputer system to operate more efficiently. A first stage of thetwo-stage approach can include predicting retention probability for thecustomer. Turning to FIG. 4B, in some embodiments activity 425 cancomprise an activity 426 of predicting a retention probability for eachof the one or more first customers using a logistic regression. In someembodiments, the predicted retention probability can be a binarydetermination of whether or not the customer will come back to theretailer.

Continuing with FIG. 4B, in some embodiments activity 425 also cancomprise an activity 427 of determining if the retention probability foreach of the one or more first customers is greater than a predeterminedthreshold value. In some embodiments, the predetermined threshold valuecan be between zero and one. By way of a non-limiting example, for abalanced set with retention percentage close to 50%, the predeterminedthreshold value can be approximately 0.5. After determining whether theretention probability for customers who have had an interaction ortransaction with the retailer within the predetermined period of time isgreater than a threshold value, those customers can be divided orcategorized into two groups: (1) customers that have had an interactionand/or transaction with the retailer within the predetermined period oftime and also have a retention probability that is greater than thethreshold value; and (2) customers that have had an interaction and/ortransaction with the retailer within the predetermined period of timebut do not have a retention probability that is greater than thethreshold value.

For customers that have had an interaction and/or transaction with theretailer within the predetermined period of time and also have aretention probability that is greater than the threshold value, thesecond stage of the two-stage approach can be applied. For example,continuing with FIG. 4B, in some embodiments activity 425 further cancomprise an activity 428 of predicting (1) a GMV value and (2) a numberof orders for each of the one or more first customers using a randomforest model if the retention probability for each of the one or morefirst customers is greater than the predetermined threshold.

For customers that have had an interaction and/or transaction with theretailer within the predetermined period of time but do not have aretention probability that is greater than the threshold value, thesecond stage of the two-stage approach is not applied and the predictedGMV and number of orders can be zero. For example, continuing with FIG.4B, in some embodiments activity 425 additionally can comprise anactivity 429 of predicting (1) a zero GMV value and (2) zero orders forany of the one or more first customers if the retention probability forthe any of the one more first customers is not greater than thepredetermined threshold.

In some embodiments, method 400 can optionally comprise an activity ofupdating the LTV update model at least once every three months. Updatingthe LTV update model can comprise (1) re-computing features and labelsfor the LTV update model utilizing the most recent available data and(2) re-calibrating parameters of the LTV update model. Updating themodel LTV update model quarterly keeps the LTV update model fresh byusing the most recent data to reflect any gradual changes in customerbehavior. In certain embodiments, the LTV update model can compriseaggregated models of a first LTV update model trained from data within asecond predetermined period of time and a second LTV update modeltrained from historical data for the second predetermined period oftime. For example, the first LTV update model can be trained using datafrom the most recent month of December, and the second LTV update modelcan be trained using data from prior months to the most recent month ofDecember.

Returning to FIG. 4A, customers that have not had an interaction ortransaction with the retailer within the predetermined period of timeare handled differently in the LTV prediction framework. The LTV ofcustomers who did not place an order or have a transaction with theretailer can sometimes follow a smooth decay function with respect to anumber of days since the last purchase or interaction. The decay patterncan be segmented and metric specific. Rather than applying the two-stageapproach using the LTV update model to update the LTV, LTVs forcustomers that have not had an interaction or transaction with theretailer within the predetermined period of time are predicted using oneor more LTV decay functions. For example, in some embodiments, method400 additionally can comprise an activity 430 of predicting, using oneor more LTV decay functions, the LTV for each of the one or more secondcustomers of the second customer group. The decay functions aredifferent from the two-stage approach of the LTV update model, and theLTV update model is not used for predicting LTV for the one or moresecond customers of the second customer group that have not had aninteraction or transaction with the retailer within the predeterminedperiod of time. In some embodiments, for example, predicting the LTV foreach of the one or more second customers of the second customer groupcan comprise predicting the LTV for each of the one or more secondcustomers of the second customer group using one or more piecewiselinear functions to estimate a decay for LTV metrics for the one or moresecond customers. In some embodiments, the decay functions can beupdated or re-calibrated quarterly.

Certain embodiments of the LTV prediction framework described herein arebeneficial to computer systems and networks. Using a sophisticated LTVupdate model, such as described herein, to update LTVs for each andevery customer in a database of a retailer can be a time and computerresource consuming activity that slows down the overall computer systemand network. By using such a sophisticated model to updated LTVs foronly those customers with transactions or interactions with the retailerwithin the predetermined amount of time, nearly all of the customers inthe database of the retailer are typically eliminated from being updatedusing the sophisticated model. For example, less than 1% of LTVs mayneed to be updated using the sophisticated model if a system onlyupdates LTVs using the sophisticated model for customers that have hadan interaction and/or transaction with the retailer within the past day.Thus, according to certain embodiments, rather than updating the LTVusing the sophisticated model for all the customers in the database ofthe retailer, which can include millions of customers, system 300 (FIG.3) needs only to update the LTV using the sophisticated model for a verysmall percentage of customers, which frees up resources of system 300for other computer network tasks. Moreover, in some embodiments adistributed network comprising distributed memory architecture is usedto retrieve customer information and/or predict LTVs for the pluralityof customers. This distributed architecture can reduce the impact on thenetwork and system resources to reduce congestion in bottlenecks whilestill allowing data to be accessible from a central location.

Returning to FIG. 4A, in some embodiments method 400 further cancomprise an activity 435 of determining an online advertisement for eachcustomer of the plurality of customers based on the LTV as predicted foreach customer of the plurality of customers. For example, certainadvertisements can target certain customers based on the LTVs of thecustomers. Accordingly, continuing with FIG. 4A, in some embodiments,method 400 also can comprise an activity 440 of coordinating a displayof the online advertisement for at least a portion of the plurality ofcustomers.

Turning ahead in the drawings, FIG. 5 illustrates a flow chart for amethod 500, according to an embodiment. Method 500 is merely exemplaryand is not limited to the embodiments presented herein. Method 500 canbe employed in many different embodiments or examples not specificallydepicted or described herein. In some embodiments, the activities ofmethod 500 can be performed in the order presented. In otherembodiments, the activities of method 500 can be performed in anysuitable order. In still other embodiments, one or more of theactivities of method 500 can be combined or skipped. In manyembodiments, system 300 (FIG. 3) can be suitable to perform method 400and/or one or more of the activities of method 500. In these or otherembodiments, one or more of the activities of method 500 can beimplemented as one or more computer instructions configured to run atone or more processing modules and configured to be stored at one ormore non-transitory memory storage modules 612, 614, 616, 618, 662,and/or 672 (FIG. 6). Such non-transitory memory storage modules can bepart of a computer system such as LTV system 310, web server 320,display system 360, and/or customer state system 370 (FIGS. 3 & 6). Theprocessing module(s) can be similar or identical to the processingmodule(s) described above with respect to computer system 100 (FIG. 1).

In certain embodiments, customers can be defined in a plurality ofcustomer states to characterize LTV growth path for the customers.Identification of LTV growth paths for customers can be useful foroverall growth of a retailer. Once customers have been defined orcategorized in one of a plurality of customer states, customers can bespecifically targeted to transition from one customer state to anothercustomer state with a higher LTV.

Identifying incremental growth of an LTV for an individual customer canbe very difficult. For example, the incremental growth of an LTV for acustomer i can be defined in a function ƒ as LTV_i=ƒ(x_i, y_i, z_i),where x_i are demographical features defining customer i, y_i arehistorical transaction features of customer i, and z_i are otherinteraction features of customer i. Identification of the incrementalLTV growth for each customer is equivalent to taking a derivative offunction ƒ. In retail, however, a machine learning trained modeltypically does not have an explicit functional form. If the machinelearning trained model does have an explicit function form, the resultsare typically non-continuous, making estimation of derivatives verydifficult.

To solve this problem, customer states can be defined, and customers canbe categorized or segmented into the customer states. Once segmented ina particular customer state, the customers can then be targeted withinparticular customer states to transition to other customer statescomprising customers with higher average LTVs. Customer states can beuseful in characterizing the future LTV status of customers, and thetransition of a customer from one customer state to another customerstate is interpretable. For example, the advancement of a customer fromone customer state to another customer state with a higher average LTVcan correspond to certain actions, such as the purchase of certainproducts with certain attributes. Moreover, the degradation of acustomer from one customer state to another customer state with a loweraverage LTV can correspond to a lack of action by the customer. Variousembodiments described herein are advantageous because the LTV growthpath of customers can be modeled as the customers' transition from onecustomer state to another customer state. The LTV growth for customersalso can be identified as a difference of average LTV between twoadjacent customer states. Moreover, the transition of customers from onecustomer state to another customer state can easily be transformed intoone or more marketing actions.

Various customer states can be defined according to differentcontemplated embodiments. For example, in one or more embodiments, theplurality of customer states can be defined as a prospect customerstate, a new customer state, a repeat customer state, an inactivecustomer state, and an active customer state. Reference is made incertain embodiments to a predetermined period of time. The predeterminedperiod of time can comprise a week, a month, three months, six months,one year, or two years in various embodiments based on the definedcustomer states. For example, in embodiments wherein the plurality ofcustomer states are defined as a prospect customer state, a new customerstate, a repeat customer state, an inactive customer state, and anactive customer state, the predetermined period of time can comprise ayear.

In some embodiments, a prospect customer state can be defined as acustomer state wherein a customer has made no purchases with theretailer. That is, the customer can be considered a prospectivecustomer. In some embodiments, a new customer state can be defined as acustomer state where a customer has made only one purchase with theretailer within the predetermined period of time and no purchases withthe retailer before the predetermined period of time. In someembodiments, a repeat customer state can be defined as a customer statewhere a customer has made two or more purchases with the retailer withinthe predetermined period of time, regardless of whether or not thecustomer has made any purchases with the retailer before thepredetermined period of time. In some embodiments, an inactive customerstate can be defined as a customer state where a customer has made nopurchases with the retailer within the predetermined period of time andone or more purchases with the retailer before the predetermined periodof time. In some embodiments, an active customer state can be defined asa customer state wherein a customer of the plurality of customer hasmade one purchase with the retailer within the predetermined period oftime and one or more purchases with the retailer before thepredetermined period of time.

By way of another non-limiting example, in one or more embodiments,customer states can be defined based on the purchase of certain productsby the customer, such as but not limited to consumable products and/ordurable products. For example, the plurality of customer states can bedefined as a consumable prospect customer state, a new consumablecustomer state, a repeat consumable customer state, an inactiveconsumable customer state, and an active consumable customer state.Customers who purchase consumable products tend to have higher LTVs thancustomers who purchase only durable products. Thus, it is advantageousto transition customers to customer states that include the purchase ofconsumable products.

As noted above, reference is made in certain embodiments to apredetermined period of time. The predetermined period of time cancomprise a week, a month, three months, six months, one year, or twoyears in various embodiments based on the defined customer states. Forexample, in embodiments where the plurality of customer states aredefined as a consumable prospect customer state, a new consumablecustomer state, a repeat consumable customer state, an inactiveconsumable customer state, and an active consumable customer state, thepredetermined period of time can comprise three months.

In some embodiments, a consumable prospect customer state can be definedas a customer state where a customer of the plurality of customers hasmade no consumable product purchases with the retailer. In someembodiments, a new consumable customer state where a customer of theplurality of customers has made one consumable product purchase with theretailer within the predetermined period of time and no consumableproduct purchases with the retailer before the predetermined period oftime. In some embodiments, a repeat consumable customer state can bedefined as a state where a customer of the plurality of customers hasmade two or more consumable product purchases with the retailer withinthe predetermined period of time, regardless of whether the customer hasmade any purchases with the retailer before the predetermined period oftime. In some embodiments, an inactive consumable customer state can bedefined as a customer state where a customer of the plurality ofcustomers has made no consumable product purchases with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime. In some embodiments, an active consumable customer state can bedefined as a customer state where a customer of the plurality ofcustomer has made one consumable product purchase with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime.

In more particular embodiments, a consumable prospect state can bedefined to include a plurality of customer sub-states. For example, inone or more embodiments a consumable prospect state can comprise aprospect customer state, a new consumable prospect customer state, arepeat consumable prospect customer state, an inactive consumableprospect customer state, and an active consumable prospect customerstate. In each of these states, a customer may have purchased a durableproduct, but not a consumable product from the retailer.

In some embodiments, a prospect customer state can be defined as acustomer state where a customer of the plurality customers has made nopurchases with the retailer. In some embodiments, a new consumableprospect (or new durable) customer state can be defined as a customerstate where a customer of the plurality of customers has made onedurable product purchase with the retailer within the predeterminedperiod of time and no durable product purchases with the retailer beforethe predetermined period of time. In some embodiments, a repeatconsumable prospect (or repeat durable) customer state can be defined asa customer state where a customer of the plurality of customers has madetwo or more durable product purchases with the retailer within thepredetermined period of time, regardless of whether or not the customerhas made any purchases with the retailer before the predetermined periodof time. In some embodiments, an inactive consumable prospect (orinactive durable) customer state can be defined as a customer statewhere a customer of the plurality of customers has made no durableproduct purchases with the retailer within the predetermined period oftime and one or more durable product purchases with the retailer beforethe predetermined period of time. In some embodiments, an activeconsumable prospect (or active durable) customer state can be defined asa customer state where a customer of the plurality of customer has madeone durable product purchase with the retailer within the predeterminedperiod of time and one or more durable product purchases with theretailer before the predetermined period of time.

Turning to FIG. 5, method 500 can comprise an activity 505 ofdetermining, for each customer of a plurality of customers, a LTV for aretailer. Determining the LTV for each customer can comprise any of theactivities described above in relation to FIGS. 4A and 4B.

Method 500 further can comprise an activity 510 of segmenting theplurality of customers into a plurality of customer states based uponone or more purchases made by each customer of the plurality ofcustomers at the retailer within a predetermined period of time. Forexample, one or more first customers of the plurality of customers canbe segmented into a first customer state of the plurality of customerstates as described above, and one or more second customers of theplurality of customers can be segmented into a second customer state ofthe plurality of customer states, as described above. The purchasescould be online purchases only, in-store purchases only, or both onlineand in-store purchases.

Once segmented into the plurality of customer states, the average LTVfor all of the customers segmented into each category can be determined.For example, method 500 further can comprise an activity 515 ofdetermining a first average LTV for the one or more first customers anda second average LTV for the one or more second customers. The averageLTV for customers segmented in certain categories can be higher than theaverage LTV for customer segmented in other categories. For example, theaverage LTV for customers segmented into a repeat consumable prospectcustomer state can be higher than the average LTV for customerssegmented into a new consumable prospect customer state and/or an activeconsumable prospect customer state. The average LTV for customerssegmented into a repeat consumable customer state also can be higherthan the average LTV for customers segmented into the repeat consumableprospect customer state and customers segmented into the new consumablecustomer state. As additional examples, the average LTV for customerscan be increasing in this order: (example 1) inactive customer state,prospect customer state, active customer state and repeat customerstate; (example 2) prospect customer state, inactive customer state, newcustomer state, active customer state, and repeat customer state;(example 3) prospect customer state, new durable customer state,inactive durable customer state, active durable customer state, newconsumable customer state, repeat durable customer state, inactiveconsumable customer state, active consumable customer state, and repeatconsumable customer state; and (example 4) prospect customer state,inactive durable customer state, new durable customer state, activedurable customer state, repeat durable customer state, inactiveconsumable customer state, new consumable customer converted fromprospect state, new consumable customer converted from durable customerstate, active consumable customer state, repeat consumable customerstate.

In some embodiments, method 500 can further comprise an activity ofallocating marketing resources to transition the one or more firstcustomers from the first customer state to the second customer state.More particularly, market resources can be allocated to transitioncustomers to the customer state comprising the highest average LTV forcustomers segmented therein. For example, because the average LTV forcustomers segmented into a repeat consumable customer state is higherthan the average LTV for customers segmented into the repeat consumableprospect customer state and customers segmented into the new consumablecustomer state, marketing resources can be allocated to transitioncustomers from the repeat consumable prospect customer state or the newconsumable customer state to the repeat consumable customer state.

In some embodiments, transition between customer states can be definedas a transition path. For example, an acquisition transition path can bea transition advancement for a customer from (1) a prospect customerstate to a new customer state and/or (2) a consumable prospect customerstate to a new consumable customer state. A retention transition pathcan be a transition for a customer from (1) a new customer state to arepeat customer state, (2) an active customer state to a repeat customerstate, (3) a new consumable customer state to a repeat consumablecustomer state, and/or (4) an inactive consumable customer state to anactive consumable customer state. A reactivation transition path can bea transition for a customer from (1) an inactive customer state to anactive customer state, and/or (2) an active consumable customer state toa repeat consumable customer state. A degradation transition path can bea transition for a customer from (1) a new customer state to an inactivecustomer state, (2) a repeat customer state to an active customer state,(3) an active customer state to an inactive customer state, (4) a newconsumable customer state to an inactive consumable customer state, (5)a repeat consumable customer state to an inactive consumable customerstate, (6) a repeat consumable customer state to an active consumablecustomer state, and/or (7) an active consumable customer state to aninactive consumable customer state.

In some embodiments, allocating marketing resources to transitioncustomers to a customer state having a higher average LTV can compriseallocating marketing resources to email advertisement campaigns,targeted advertisements on social media, search engine marketing,customizing advertisements on an advertisement carousel on the websiteof the retailer, targeted advertisements on websites not associated oraffiliated with the retailer, and the like. In each of these examples,the advertisement can be specifically configured to target userssegmented in one customer state and transition the customer to anothercustomer state having a higher average LTV. Thus, the advertisement canbe different depending on the customer state for the customer. In someembodiments, system 300 (FIG. 3) can tag or otherwise identify customersafter visiting the website of the retailer and record computeridentification information (such as cookies) for the customers when theone or more first customers and the one or more second customers visit awebsite of the retailer.

In some embodiments, a distributed network comprising distributed memoryarchitecture is used to retrieve advertisements and/or retrieve customerinformation for segmenting of the plurality of customers. Thisdistributed architecture can reduce the impact on the network and systemresources to reduce congestion in bottlenecks while still allowing datato be accessible from a central location.

Returning to FIG. 5, method 500 further can comprise an activity 520 ofcoordinating a first display of a first online advertisement for the oneor more first customers to transition the one or more first customersfrom the first customer state to the second customer state, and also anactivity 525 of coordinating a second display of a second onlineadvertisement for the one or more second customers to transition the oneor more second customers to a customer state comprising a higher orhighest LTV average. Because the advertisements can be targeted based onthe customer state to which a customer is segmented, the first onlineadvertisement and the second online advertisement can be different. Forexample, if the first customer is segmented in a new consumable prospectcustomer state and if the second customer is segmented in a repeatconsumable customer state, the first advertisement for the firstcustomer may be for a consumable product, and the second advertisementfor the second customer may be for a durable product.

In more particular embodiments, coordinating the first display of thefirst online advertisement can comprise coordinating, using the computeridentification of the one or more first customers, the first display ofthe first online advertisement for the one or more first customers on anoffsite webpage that is not affiliated with the website of the retailerwhen the one or more first customers visit the offsite webpage. Theoffsite webpage can be a third-party social media webpage, a searchengine webpage, or other third-party webpage. In these and otherembodiments, coordinating the second display of the second onlineadvertisement can comprise coordinating, using the computeridentification of the one or more second customers, the second displayof the second online advertisement for the one or more second customerson the offsite webpage when the one or more second customers visit theoffsite webpage.

In some particular embodiments, coordinating the first display of thefirst online advertisement can comprise coordinating, using the computeridentification of the one or more first customers, the first display ofthe first online advertisement for the one or more first customers on anadvertisement carousel on the website of the retailer when the one ormore first customers visit the website of the retailer. In these andother embodiments, coordinating the second display of the second onlineadvertisement can comprise coordinating, using the computeridentification of the one or more second customers, the second displayof the second online advertisement for the one or more second customerson the advertisement carousel on the web site of the retailer when theone or more second customers visit the website of the retailer.

In some embodiments coordinating the first display of the first onlineadvertisement can comprise coordinating the first display of the firstonline advertisement for the one or more first customers in a firstemail sent to the one or more first customers. In these and otherembodiments, coordinating the second display of the second onlineadvertisement can comprise coordinating the second display of the secondonline advertisement for the one or more second customers in a secondemail sent to the one or more second customers.

FIG. 6 illustrates a block diagram of a portion of system 300 comprisingLTV system 310, web server 320, display system 360, and/or customerstate system 370, according to the embodiment shown in FIG. 3. Each ofLTV system 310, web server 320, display system 360, and/or customerstate system 370, is merely exemplary and not limited to the embodimentspresented herein. Each of LTV system 310, web server 320, display system360, and/or customer state system 370, can be employed in many differentembodiments or examples not specifically depicted or described herein.In some embodiments, certain elements or modules of LTV system 310, webserver 320, display system 360, and/or customer state system 370, canperform various procedures, processes, and/or acts. In otherembodiments, the procedures, processes, and/or acts can be performed byother suitable elements or modules.

In many embodiments, LTV system 310 can comprise non-transitory memorystorage modules 612, 614, 616, and 618. Memory storage module 612 can bereferred to as customer information module 612. In many embodiments,customer information module 612 can store computing instructionsconfigured to run on one or more processing modules and perform one ormore acts of method 400 (FIGS. 4A-4B) (e.g., activity 405 of storingcustomer information in a customer database of a retailer (FIG. 4A), andactivity 410 of determining whether each customer of the plurality ofcustomers had (1) an online store transaction with the retailer, (2) anoffline store transaction with the retailer, or (3) an onlineinteraction with the retailer within a first predetermined period oftime (FIG. 4A)).

Memory storage module 614 can be referred to as categorization module614. In many embodiments, categorization module 614 can store computinginstructions configured to run on one or more processing modules andperform one or more acts of method 400 (FIGS. 4A-4B) (e.g. activity 415of categorizing one or more first customers of the plurality ofcustomers into a first customer group if the one or more first customershad (1) the online store transaction with the retailer, (2) the offlinestore transaction with the retailer, or (3) the online interaction withthe retailer within the first predetermined period of time (FIG. 4A),and activity 420 of categorizing one or more second customers of theplurality of customers into a second customer group if the one or moresecond customers did not have (1) the online store transaction with theretailer, (2) the offline store transaction with the retailer, or (3)the online interaction with the retailer within the first predeterminedperiod of time (FIG. 4A)).

Memory storage module 616 can be referred to as prediction module 616.In many embodiments, prediction module 616 can store computinginstructions configured to run on one or more processing modules andperform one or more acts of method 400 (FIGS. 4A-4B) (e.g. activity 425of predicting, using a LTV update model, a LTV for each of the one ormore first customers of the first customer group (FIG. 4A), which caninclude activity 426 of predicting a retention probability for each ofthe one or more first customers using a logistic regression (FIG. 4B),activity 427 of determining if the retention probability for each of theone or more first customers is greater than a predetermined thresholdvalue (FIG. 4B), activity 428 of predicting (1) a GMV value and (2) anumber of orders for each of the one or more first customers using arandom forest model if the retention probability for each of the one ormore first customers is greater than the predetermined threshold, andactivity 429 of predicting (1) a zero GMV value and (2) zero orders forany of the one or more first customers if the retention probability forthe any of the one more first customers is not greater than thepredetermined threshold (FIG. 4B), and activity 430 of predicting, usingone or more LTV decay functions, the LTV for each of the one or moresecond customers of the second customer group (FIG. 4A)).

Memory storage module 618 can be referred to as advertisement module618. In many embodiments, advertisement module 618 can store computinginstructions configured to run on one or more processing modules andperform one or more acts of method 400 (FIGS. 4A-4B) (e.g. activity 435of determining an online advertisement for each customer of theplurality of customers based on the LTV as predicted for each customerof the plurality of customers (FIG. 4A)).

In many embodiments, one or more non-transitory memory storage modules612, 614, 616, and 618 of LTV system 310 can store computing instructionconfigured to run on one or more processing modules and perform one ormore acts of method 500 (FIG. 5) (e.g. activity 505 of determining, foreach customer of a plurality of customers, a LTV for a retailer (FIG.5)).

In many embodiments, customer state system 370 can comprisenon-transitory memory storage module 672. Memory storage module 672 canbe referred to as segmenting module 672. In many embodiments, segmentingmodule 672 can store computing instructions configured to run on one ormore processing modules and perform one or more acts of method 500 (FIG.5) (e.g., activity 510 of segmenting the plurality of customers into aplurality of customer states based upon one or more purchases made byeach customer of the plurality of customers at the retailer within apredetermined period of time (FIG. 5), and activity 515 of determining afirst average LTV for the one or more first customers and a secondaverage LTV for the one or more second customers (FIG. 5)).

In many embodiments, display system 360 can comprise non-transitorymemory storage module 662. Memory storage module 662 can be referred toas display module 662. In many embodiments, display module 662 can storecomputing instructions configured to run on one or more processingmodules and perform one or more acts of methods 400 and 500 (FIGS. 4A,4B, and 5) (e.g., activity 440 of coordinating a display of the onlineadvertisement for at least a portion of the plurality of customers (FIG.4A), activity 520 of coordinating a first display of a first onlineadvertisement for the one or more first customers to transition the oneor more first customers from the first customer state to the secondcustomer state (FIG. 5), and activity 525 of coordinating a seconddisplay of a second online advertisement for the one or more secondcustomers (FIG. 5)).

Although systems and methods for determining customer LTV and customerstate transitions for growth of customer LTV have been described withreference to specific embodiments, it will be understood by thoseskilled in the art that various changes may be made without departingfrom the spirit or scope of the disclosure. Accordingly, the disclosureof embodiments is intended to be illustrative of the scope of thedisclosure and is not intended to be limiting. It is intended that thescope of the disclosure shall be limited only to the extent required bythe appended claims. For example, to one of ordinary skill in the art,it will be readily apparent that any element of FIGS. 1-6 may bemodified, and that the foregoing discussion of certain of theseembodiments does not necessarily represent a complete description of allpossible embodiments. For example, one or more of the procedures,processes, or activities of FIGS. 4A-B and 5 may include differentprocedures, processes, and/or activities and be performed by manydifferent modules, in many different orders.

All elements claimed in any particular claim are essential to theembodiment claimed in that particular claim. Consequently, replacementof one or more claimed elements constitutes reconstruction and notrepair. Additionally, benefits, other advantages, and solutions toproblems have been described with regard to specific embodiments. Thebenefits, advantages, solutions to problems, and any element or elementsthat may cause any benefit, advantage, or solution to occur or becomemore pronounced, however, are not to be construed as critical, required,or essential features or elements of any or all of the claims, unlesssuch benefits, advantages, solutions, or elements are stated in suchclaim.

Moreover, embodiments and limitations disclosed herein are not dedicatedto the public under the doctrine of dedication if the embodiments and/orlimitations: (1) are not expressly claimed in the claims; and (2) are orare potentially equivalents of express elements and/or limitations inthe claims under the doctrine of equivalents.

What is claimed is:
 1. A system comprising: one or more processingmodules; and one or more non-transitory storage modules storingcomputing instructions configured to run on the one or more processingmodules and perform acts of: determining, for each customer of aplurality of customers, a lifetime value (LTV) for a retailer;segmenting the plurality of customers into a plurality of customerstates based upon one or more purchases made by each customer of theplurality of customers at the retailer within a predetermined period oftime such that one or more first customers of the plurality of customersare segmented into a first customer state of the plurality of customerstates and one or more second customers of the plurality of customersare segmented into a second customer state of the plurality of customerstates; determining a first average LTV for the one or more firstcustomers and a second average LTV for the one or more second customers,wherein the first average LTV is a lower number than the second LTV;coordinating a first display of a first online advertisement for the oneor more first customers to transition the one or more first customersfrom the first customer state to the second customer state; andcoordinating a second display of a second online advertisement for theone or more second customers.
 2. The system of claim 1, wherein the oneor more non-transitory storage modules storing the computinginstructions are further configured to run on the one or more processingmodules and perform an act of allocating marketing resources totransition the one or more first customers from the first customer stateto the second customer state.
 3. The system of claim 1, wherein the oneor more non-transitory storage modules storing the computinginstructions are further configured to run on the one or more processingmodules and perform an act of recording computer identificationinformation for the one or more first customers and the one or moresecond customers when the one or more first customers and the one ormore second customers visit a website of the retailer.
 4. The system ofclaim 3, wherein: coordinating the first display of the first onlineadvertisement comprises: coordinating, using the computer identificationof the one or more first customers, the first display of the firstonline advertisement for the one or more first customers on an offsitewebpage that is not affiliated with the website of the retailer when theone or more first customers visit the offsite webpage; and coordinatingthe second display of the second online advertisement comprises:coordinating, using the computer identification of the one or moresecond customers, the second display of the second online advertisementfor the one or more second customers on the offsite webpage when the oneor more second customers visit the offsite webpage.
 5. The system ofclaim 3, wherein: coordinating the first display of the first onlineadvertisement comprises: coordinating, using the computer identificationof the one or more first customers, the first display of the firstonline advertisement for the one or more first customers on anadvertisement carousel on the website of the retailer when the one ormore first customers visit the website of the retailer; and coordinatingthe second display of the second online advertisement comprises:coordinating, using the computer identification of the one or moresecond customers, the second display of the second online advertisementfor the one or more second customers on the advertisement carousel onthe website of the retailer when the one or more second customers visitthe website of the retailer.
 6. The system of claim 1, wherein:coordinating the first display of the first online advertisementcomprises: coordinating the first display of the first onlineadvertisement for the one or more first customers in a first email sentto the one or more first customers; and coordinating the second displayof the second online advertisement comprises: coordinating the seconddisplay of the second online advertisement for the one or more secondcustomers in a second email sent to the one or more second customers. 7.The system of claim 1, wherein the plurality of customer statescomprises: a prospect customer state wherein a customer of the pluralitycustomers has made no purchases with the retailer; a new customer statewherein a customer of the plurality of customers has made one purchasewith the retailer within the predetermined period of time and nopurchases with the retailer before the predetermined period of time; arepeat customer state wherein a customer of the plurality of customershas made two or more purchases with the retailer within thepredetermined period of time; an inactive customer state wherein acustomer of the plurality of customers has made no purchases with theretailer within the predetermined period of time and one or morepurchases with the retailer before the predetermined period of time; andan active customer state wherein a customer of the plurality of customerhas made one purchase with the retailer within the predetermined periodof time and one or more purchases with the retailer before thepredetermined period of time.
 8. The system of claim 1, wherein theplurality of customer states comprises: a consumable prospect customerstate wherein a customer of the plurality of customers has made noconsumable product purchases with the retailer; a new consumablecustomer state wherein a customer of the plurality of customers has madeone consumable product purchase with the retailer within thepredetermined period of time and no consumable product purchases withthe retailer before the predetermined period of time; a repeatconsumable customer state wherein a customer of the plurality ofcustomers has made two or more consumable product purchases with theretailer within the predetermined period of time; an inactive consumablecustomer state wherein a customer of the plurality of customers has madeno consumable product purchases with the retailer within thepredetermined period of time and one or more consumable productpurchases with the retailer before the predetermined period of time; andan active consumable customer state wherein a customer of the pluralityof customer has made one consumable product purchase with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime.
 9. The system of claim 8, wherein the consumable prospect customerstate comprises: a prospect customer state wherein a customer of theplurality customers has made no purchases with the retailer; a newconsumable prospect customer state wherein a customer of the pluralityof customers has made one durable product purchase with the retailerwithin the predetermined period of time and no durable product purchaseswith the retailer before the predetermined period of time; a repeatconsumable prospect customer state wherein a customer of the pluralityof customers has made two or more durable product purchases with theretailer within the predetermined period of time; an inactive consumableprospect customer state wherein a customer of the plurality of customershas made no durable product purchases with the retailer within thepredetermined period of time and one or more durable product purchaseswith the retailer before the predetermined period of time; and an activeconsumable prospect customer state wherein a customer of the pluralityof customer has made one durable product purchase with the retailerwithin the predetermined period of time and one or more durable productpurchases with the retailer before the predetermined period of time. 10.The system of claim 1, wherein: the one or more non-transitory storagemodules storing the computing instructions are further configured to runon the one or more processing modules and perform acts of: allocatingmarketing resources to transition the one or more first customers fromthe first customer state to the second customer state; and recordingcomputer identification information for the one or more first customersand the one or more second customers when the one or more firstcustomers and the one or more second customers visit a website of theretailer; coordinating the first display of the first onlineadvertisement comprises at least one of: coordinating, using thecomputer identification of the one or more first customers, the firstdisplay of the first online advertisement for the one or more firstcustomers on an offsite webpage that is not affiliated with the websiteof the retailer when the one or more first customers visit the offsitewebpage; coordinating, using the computer identification of the one ormore first customers, the first display of the first onlineadvertisement for the one or more first customers on an advertisementcarousel on the website of the retailer when the one or more firstcustomers visit the website of the retailer; and coordinating the firstdisplay of the first online advertisement for the one or more firstcustomers in a first email sent to the one or more first customers;coordinating the second display of the second online advertisementcomprises at least one of: coordinating, using the computeridentification of the one or more second customers, the second displayof the second online advertisement for the one or more second customerson the offsite webpage when the one or more second customers visit theoffsite webpage; coordinating, using the computer identification of theone or more second customers, the second display of the second onlineadvertisement for the one or more second customers on the advertisementcarousel of the website of the retailer when the one or more secondcustomers visit the website of the retailer; and coordinating the seconddisplay of the second online advertisement for the one or more secondcustomers in a second email sent to the one or more second customers;and the plurality of customer states comprises: a new consumablecustomer state wherein a customer of the plurality of customers has madeone consumable product purchase with the retailer within thepredetermined period of time and no consumable product purchases withthe retailer before the predetermined period of time; a repeatconsumable customer state wherein a customer of the plurality ofcustomers has made two or more consumable product purchases with theretailer within the predetermined period of time; an inactive consumablecustomer state wherein a customer of the plurality of customers has madeno consumable product purchases with the retailer within thepredetermined period of time and one or more consumable productpurchases with the retailer before the predetermined period of time; anactive consumable customer state wherein a customer of the plurality ofcustomer has made one consumable product purchase with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime; and a consumable prospect customer state wherein a customer of theplurality of customers has made no consumable product purchases with theretailer, the consumable prospect customer state comprising: a prospectcustomer state wherein a customer of the plurality customers has made nopurchases with the retailer; a new consumable prospect customer statewherein a customer of the plurality of customers has made one durableproduct purchase with the retailer within the predetermined period oftime and no durable product purchases with the retailer before thepredetermined period of time; a repeat consumable prospect customerstate wherein a customer of the plurality of customers has made two ormore durable product purchases with the retailer within thepredetermined period of time; an inactive consumable prospect customerstate wherein a customer of the plurality of customers has made nodurable product purchases with the retailer within the predeterminedperiod of time and one or more durable product purchases with theretailer before the predetermined period of time; and an activeconsumable prospect customer state wherein a customer of the pluralityof customer has made one durable product purchase with the retailerwithin the predetermined period of time and one or more durable productpurchases with the retailer before the predetermined period of time. 11.A method comprising: determining, for each customer of a plurality ofcustomers, a lifetime value (LTV) for a retailer; segmenting theplurality of customers into a plurality of customer states based uponone or more purchases made by each customer of the plurality ofcustomers at the retailer within a predetermined period of time suchthat one or more first customers of the plurality of customers aresegmented into a first customer state of the plurality of customerstates and one or more second customers of the plurality of customersare segmented into a second customer state of the plurality of customerstates; determining a first average LTV for the one or more firstcustomers and a second average LTV for the one or more second customers,wherein the first average LTV is a lower number than the second LTV;coordinating a first display of a first online advertisement for the oneor more first customers to transition the one or more first customersfrom the first customer state to the second customer state; andcoordinating a second display of a second online advertisement for theone or more second customers.
 12. The method of claim 11, furthercomprising allocating marketing resources to transition the one or morefirst customers from the first customer state to the second customerstate.
 13. The method of claim 11, further comprising recording computeridentification information for the one or more first customers and theone or more second customers when the one or more first customers andthe one or more second customers visit a website of the retailer. 14.The method of claim 13, wherein: coordinating the first display of thefirst online advertisement comprises: coordinating, using the computeridentification of the one or more first customers, the first display ofthe first online advertisement for the one or more first customers on anoffsite webpage that is not affiliated with the website of the retailerwhen the one or more first customers visit the offsite webpage; andcoordinating the second display of the second online advertisementcomprises: coordinating, using the computer identification of the one ormore second customers, the second display of the second onlineadvertisement for the one or more second customers on the offsitewebpage when the one or more second customers visit the offsite webpage.15. The method of claim 13, wherein: coordinating the first display ofthe first online advertisement comprises: coordinating, using thecomputer identification of the one or more first customers, the firstdisplay of the first online advertisement for the one or more firstcustomers on an advertisement carousel on the website of the retailerwhen the one or more first customers visit the website of the retailer;and coordinating the second display of the second online advertisementcomprises: coordinating, using the computer identification of the one ormore second customers, the second display of the second onlineadvertisement for the one or more second customers on the advertisementcarousel on the website of the retailer when the one or more secondcustomers visit the website of the retailer.
 16. The method of claim 11,wherein: coordinating the first display of the first onlineadvertisement comprises: coordinating the first display of the firstonline advertisement for the one or more first customers in a firstemail sent to the one or more first customers; and coordinating thesecond display of the second online advertisement comprises:coordinating the second display of the second online advertisement forthe one or more second customers in a second email sent to the one ormore second customers.
 17. The method of claim 11, wherein the pluralityof customer states comprises: a prospect customer state wherein acustomer of the plurality customers has made no purchases with theretailer; a new customer state wherein a customer of the plurality ofcustomers has made one purchase with the retailer within thepredetermined period of time and no purchases with the retailer beforethe predetermined period of time; a repeat customer state wherein acustomer of the plurality of customers has made two or more purchaseswith the retailer within the predetermined period of time; an inactivecustomer state wherein a customer of the plurality of customers has madeno purchases with the retailer within the predetermined period of timeand one or more purchases with the retailer before the predeterminedperiod of time; and an active customer state wherein a customer of theplurality of customer has made one purchase with the retailer within thepredetermined period of time and one or more purchases with the retailerbefore the predetermined period of time.
 18. The method of claim 11,wherein the plurality of customer states comprises: a consumableprospect customer state wherein a customer of the plurality of customershas made no consumable product purchases with the retailer; a newconsumable customer state wherein a customer of the plurality ofcustomers has made one consumable product purchase with the retailerwithin the predetermined period of time and no consumable productpurchases with the retailer before the predetermined period of time; arepeat consumable customer state wherein a customer of the plurality ofcustomers has made two or more consumable product purchases with theretailer within the predetermined period of time; an inactive consumablecustomer state wherein a customer of the plurality of customers has madeno consumable product purchases with the retailer within thepredetermined period of time and one or more consumable productpurchases with the retailer before the predetermined period of time; andan active consumable customer state wherein a customer of the pluralityof customer has made one consumable product purchase with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime.
 19. The method of claim 18, wherein the consumable prospectcustomer state comprises: a prospect customer state wherein a customerof the plurality customers has made no purchases with the retailer; anew consumable prospect customer state wherein a customer of theplurality of customers has made one durable product purchase with theretailer within the predetermined period of time and no durable productpurchases with the retailer before the predetermined period of time; arepeat consumable prospect customer state wherein a customer of theplurality of customers has made two or more durable product purchaseswith the retailer within the predetermined period of time; an inactiveconsumable prospect customer state wherein a customer of the pluralityof customers has made no durable product purchases with the retailerwithin the predetermined period of time and one or more durable productpurchases with the retailer before the predetermined period of time; andan active consumable prospect customer state wherein a customer of theplurality of customer has made one durable product purchase with theretailer within the predetermined period of time and one or more durableproduct purchases with the retailer before the predetermined period oftime.
 20. The method of claim 11, wherein: the method further comprises:allocating marketing resources to transition the one or more firstcustomers from the first customer state to the second customer state;and recording computer identification information for the one or morefirst customers and the one or more second customers when the one ormore first customers and the one or more second customers visit awebsite of the retailer; coordinating the first display of the firstonline advertisement comprises at least one of: coordinating, using thecomputer identification of the one or more first customers, the firstdisplay of the first online advertisement for the one or more firstcustomers on an offsite webpage that is not affiliated with the websiteof the retailer when the one or more first customers visit the offsitewebpage; coordinating, using the computer identification of the one ormore first customers, the first display of the first onlineadvertisement for the one or more first customers on an advertisementcarousel on the website of the retailer when the one or more firstcustomers visit the website of the retailer; and coordinating the firstdisplay of the first online advertisement for the one or more firstcustomers in a first email sent to the one or more first customers;coordinating the second display of the second online advertisementcomprises at least one of: coordinating, using the computeridentification of the one or more second customers, the second displayof the second online advertisement for the one or more second customerson the offsite webpage when the one or more second customers visit theoffsite webpage; coordinating, using the computer identification of theone or more second customers, the second display of the second onlineadvertisement for the one or more second customers on the advertisementcarousel of the website of the retailer when the one or more secondcustomers visit the website of the retailer; and coordinating the seconddisplay of the second online advertisement for the one or more secondcustomers in a second email sent to the one or more second customers;and the plurality of customer states comprises: a new consumablecustomer state wherein a customer of the plurality of customers has madeone consumable product purchase with the retailer within thepredetermined period of time and no consumable product purchases withthe retailer before the predetermined period of time; a repeatconsumable customer state wherein a customer of the plurality ofcustomers has made two or more consumable product purchases with theretailer within the predetermined period of time; an inactive consumablecustomer state wherein a customer of the plurality of customers has madeno consumable product purchases with the retailer within thepredetermined period of time and one or more consumable productpurchases with the retailer before the predetermined period of time; anactive consumable customer state wherein a customer of the plurality ofcustomer has made one consumable product purchase with the retailerwithin the predetermined period of time and one or more consumableproduct purchases with the retailer before the predetermined period oftime; and a consumable prospect customer state wherein a customer of theplurality of customers has made no consumable product purchases with theretailer, the consumable prospect customer state comprising: a prospectcustomer state wherein a customer of the plurality customers has made nopurchases with the retailer; a new consumable prospect customer statewherein a customer of the plurality of customers has made one durableproduct purchase with the retailer within the predetermined period oftime and no durable product purchases with the retailer before thepredetermined period of time; a repeat consumable prospect customerstate wherein a customer of the plurality of customers has made two ormore durable product purchases with the retailer within thepredetermined period of time; an inactive consumable prospect customerstate wherein a customer of the plurality of customers has made nodurable product purchases with the retailer within the predeterminedperiod of time and one or more durable product purchases with theretailer before the predetermined period of time; and an activeconsumable prospect customer state wherein a customer of the pluralityof customer has made one durable product purchase with the retailerwithin the predetermined period of time and one or more durable productpurchases with the retailer before the predetermined period of time.